scholarly journals The Role of Single-Cell Technology in the Study and Control of Infectious Diseases

Cells ◽  
2020 ◽  
Vol 9 (6) ◽  
pp. 1440 ◽  
Author(s):  
Weikang Nicholas Lin ◽  
Matthew Zirui Tay ◽  
Ri Lu ◽  
Yi Liu ◽  
Chia-Hung Chen ◽  
...  
Keyword(s):  
Infectious Diseases ◽  
Single Cell ◽  
Single Cell Analysis ◽  
Treatment Options ◽  
Recent Decade ◽  
Cellular Heterogeneity ◽  
Biological Studies ◽  
Infection Mechanisms ◽  
Next Generation Sequencing Ngs ◽  
And Control

The advent of single-cell research in the recent decade has allowed biological studies at an unprecedented resolution and scale. In particular, single-cell analysis techniques such as Next-Generation Sequencing (NGS) and Fluorescence-Activated Cell Sorting (FACS) have helped show substantial links between cellular heterogeneity and infectious disease progression. The extensive characterization of genomic and phenotypic biomarkers, in addition to host–pathogen interactions at the single-cell level, has resulted in the discovery of previously unknown infection mechanisms as well as potential treatment options. In this article, we review the various single-cell technologies and their applications in the ongoing fight against infectious diseases, as well as discuss the potential opportunities for future development.

scholarly journals Comprehensive analysis of single cell ATAC-seq data with SnapATAC

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Rongxin Fang ◽  
Sebastian Preissl ◽  
Yang Li ◽  
Xiaomeng Hou ◽  
Jacinta Lucero ◽  
...  
Keyword(s):  
Single Cell ◽  
Single Cell Analysis ◽  
Expression Patterns ◽  
Regulatory Elements ◽  
Cellular Heterogeneity ◽  
Specific Gene ◽  
Open Chromatin ◽  
Cell Type ◽  
Process Data ◽  
Cell Type Specific

AbstractIdentification of the cis-regulatory elements controlling cell-type specific gene expression patterns is essential for understanding the origin of cellular diversity. Conventional assays to map regulatory elements via open chromatin analysis of primary tissues is hindered by sample heterogeneity. Single cell analysis of accessible chromatin (scATAC-seq) can overcome this limitation. However, the high-level noise of each single cell profile and the large volume of data pose unique computational challenges. Here, we introduce SnapATAC, a software package for analyzing scATAC-seq datasets. SnapATAC dissects cellular heterogeneity in an unbiased manner and map the trajectories of cellular states. Using the Nyström method, SnapATAC can process data from up to a million cells. Furthermore, SnapATAC incorporates existing tools into a comprehensive package for analyzing single cell ATAC-seq dataset. As demonstration of its utility, SnapATAC is applied to 55,592 single-nucleus ATAC-seq profiles from the mouse secondary motor cortex. The analysis reveals ~370,000 candidate regulatory elements in 31 distinct cell populations in this brain region and inferred candidate cell-type specific transcriptional regulators.

scholarly journals Single-cell analysis reveals cellular heterogeneity and molecular determinants of hypothalamic leptin-receptor cells

2020 ◽  
Author(s):  
N. Kakava-Georgiadou ◽  
J.F. Severens ◽  
A.M. Jørgensen ◽  
K.M. Garner ◽  
M.C.M Luijendijk ◽  
...  
Keyword(s):  
Single Cell ◽  
Leptin Receptor ◽  
Single Cell Analysis ◽  
Cell Types ◽  
Cellular Heterogeneity ◽  
Molecular Signature ◽  
Neuronal Populations ◽  
Hypothalamic Nuclei ◽  
Satiety Hormone ◽  
Multiple Cell

AbstractHypothalamic nuclei which regulate homeostatic functions express leptin receptor (LepR), the primary target of the satiety hormone leptin. Single-cell RNA sequencing (scRNA-seq) has facilitated the discovery of a variety of hypothalamic cell types. However, low abundance of LepR transcripts prevented further characterization of LepR cells. Therefore, we perform scRNA-seq on isolated LepR cells and identify eight neuronal clusters, including three uncharacterized Trh-expressing populations as well as 17 non-neuronal populations including tanycytes, oligodendrocytes and endothelial cells. Food restriction had a major impact on Agrp neurons and changed the expression of obesity-associated genes. Multiple cell clusters were enriched for GWAS signals of obesity. We further explored changes in the gene regulatory landscape of LepR cell types. We thus reveal the molecular signature of distinct populations with diverse neurochemical profiles, which will aid efforts to illuminate the multi-functional nature of leptin’s action in the hypothalamus.

CNS myeloid cell heterogeneity at the single-cell level

Neuroforum ◽  
2019 ◽  
Vol 25 (3) ◽  
pp. 195-204
Author(s):  
Chotima Böttcher ◽  
Roman Sankowski ◽  
Josef Priller ◽  
Marco Prinz
Keyword(s):  
Single Cell ◽  
Single Cell Analysis ◽  
Myeloid Cell ◽  
Cellular Heterogeneity ◽  
Cell Heterogeneity ◽  
Mass Cytometry ◽  
Dynamic Regulation ◽  
The Central Nervous System ◽  
Disease Profiling ◽  
The Brain

Abstract The cellular composition of the central nervous system (CNS) is highly complex and dynamic. Regulation of this complexity is increasingly recognized to be spatially and temporally dependent during development, homeostasis and disease. Context-dependent cellular heterogeneity was shown for neuroectodermal cells as well as the myeloid compartment of the CNS. The brain myeloid compartment comprises microglia and other CNS-associated macrophages. These are brain-resident cells with critical roles in brain development, maintenance, and immune responses during states of disease. Profiling of CNS myeloid cell heterogeneity has been greatly facilitated in the past years by development of high-throughput technologies for single-cell analysis. This review summarizes current insights into heterogeneity of the CNS myeloid cell population determined by single-cell RNA sequencing and mass cytometry. The results offer invaluable insights into CNS biology and will facilitate the development of therapies for neurodegenerative and neuroinflammatory pathologies.

scholarly journals Single-Cell Analysis of Antigen-Specific CD8+ T-Cell Transcripts Reveals Profiles Specific to mRNA or Adjuvanted Protein Vaccines

2021 ◽  
Vol 12 ◽  
Author(s):  
Trine Sundebo Meldgaard ◽  
Fabiola Blengio ◽  
Denise Maffione ◽  
Chiara Sammicheli ◽  
Simona Tavarini ◽  
...  
Keyword(s):  
T Cells ◽  
T Cell ◽  
Single Cell ◽  
Cd8 T Cells ◽  
Single Cell Analysis ◽  
Expression Profiles ◽  
Cd8 T Cell ◽  
Cellular Heterogeneity ◽  
Cell Analysis

CD8+ T cells play a key role in mediating protective immunity after immune challenges such as infection or vaccination. Several subsets of differentiated CD8+ T cells have been identified, however, a deeper understanding of the molecular mechanism that underlies T-cell differentiation is lacking. Conventional approaches to the study of immune responses are typically limited to the analysis of bulk groups of cells that mask the cells’ heterogeneity (RNA-seq, microarray) and to the assessment of a relatively limited number of biomarkers that can be evaluated simultaneously at the population level (flow and mass cytometry). Single-cell analysis, on the other hand, represents a possible alternative that enables a deeper characterization of the underlying cellular heterogeneity. In this study, a murine model was used to characterize immunodominant hemagglutinin (HA533-541)-specific CD8+ T-cell responses to nucleic- and protein-based influenza vaccine candidates, using single-cell sorting followed by transcriptomic analysis. Investigation of single-cell gene expression profiles enabled the discovery of unique subsets of CD8+ T cells that co-expressed cytotoxic genes after vaccination. Moreover, this method enabled the characterization of antigen specific CD8+ T cells that were previously undetected. Single-cell transcriptome profiling has the potential to allow for qualitative discrimination of cells, which could lead to novel insights on biological pathways involved in cellular responses. This approach could be further validated and allow for more informed decision making in preclinical and clinical settings.

scholarly journals Optimized Data-Independent Acquisition Approach for Proteomic Analysis at Single-Cell Level

2021 ◽  
Author(s):  
Yuefan Wang ◽  
Tung-Shing Mamie Lih ◽  
Lijun Chen ◽  
Yuanwei Xu ◽  
Morgan D. Kuczler ◽  
...  
Keyword(s):  
Single Cell ◽  
Proteomic Analysis ◽  
Single Cell Analysis ◽  
Cancer Cell Line ◽  
Cellular Heterogeneity ◽  
Single Cell Level ◽  
Cell Level ◽  
Data Independent Acquisition ◽  
Peptide Precursors ◽  
Proteomic Study

Abstract Background: Single-cell proteomic analysis provides valuable insights into cellular heterogeneity allowing the characterization of the cellular microenvironment which is difficult to accomplish in bulk proteomic analysis. Currently, single-cell proteomic studies utilize data-dependent acquisition (DDA) mass spectrometry (MS) coupled with a TMT labelled carrier channel. Due to the extremely imbalanced MS signals among the carrier channel and other TMT reporter ions, the quantification is compromised. Thus, data-independent acquisition (DIA)-MS should be considered as an alternative approach towards single-cell proteomic study since it generates reproducible quantitative data. However, there are limited reports on the optimal workflow for DIA-MS-based single-cell analysis. Methods: We report an optimized DIA workflow for single-cell proteomics using Orbitrap Lumos Tribrid instrument. We utilized a breast cancer cell line (MDA-MB-231) and induced drug resistant polyaneuploid cancer cells (PACCs) to evaluate our established workflow. Results: We found that a short LC gradient was preferable for peptides extracted from single cell level with less than 2 ng sample amount. The total number of co-searching peptide precursors was also critical for protein and peptide identifications at nano- and sub-nano-gram levels. Post-translationally modified peptides could be identified from a nano-gram level of peptides. Using the optimized workflow, up to 1,500 protein groups were identified from a single PACC corresponding to 0.2 ng of peptides. Furthermore, about 200 peptides with phosphorylation, acetylation, and ubiquitination were identified from global DIA analysis of 100 cisplatin resistant PACCs (20 ng). Finally, we used this optimized DIA approach to compare the whole proteome of MDA-MB-231 parental cells and induced PACCs at a single-cell level. We found the single-cell level comparison could reflect real protein expression changes and identify the protein copy number. Conclusions: Our results demonstrate that the optimized DIA pipeline can serve as a reliable quantitative tool for single-cell as well as sub-nano-gram proteomic analysis.

scholarly journals Single-cell analysis of the cellular heterogeneity and interactions in the injured mouse spinal cord

2021 ◽  
Vol 218 (8) ◽  
Author(s):  
Lindsay M. Milich ◽  
James S. Choi ◽  
Christine Ryan ◽  
Susana R. Cerqueira ◽  
Sofia Benavides ◽  
...  
Keyword(s):  
Spinal Cord ◽  
Spinal Cord Injury ◽  
Single Cell ◽  
Single Cell Analysis ◽  
Healing Process ◽  
Cellular Heterogeneity ◽  
Wound Healing Process ◽  
Cellular Interactions ◽  
Mouse Spinal Cord ◽  
Cord Injury

The wound healing process that occurs after spinal cord injury is critical for maintaining tissue homeostasis and limiting tissue damage, but eventually results in a scar-like environment that is not conducive to regeneration and repair. A better understanding of this dichotomy is critical to developing effective therapeutics that target the appropriate pathobiology, but a major challenge has been the large cellular heterogeneity that results in immensely complex cellular interactions. In this study, we used single-cell RNA sequencing to assess virtually all cell types that comprise the mouse spinal cord injury site. In addition to discovering novel subpopulations, we used expression values of receptor–ligand pairs to identify signaling pathways that are predicted to regulate specific cellular interactions during angiogenesis, gliosis, and fibrosis. Our dataset is a valuable resource that provides novel mechanistic insight into the pathobiology of not only spinal cord injury but also other traumatic disorders of the CNS.

scholarly journals Studying Kidney Diseases at the Single-Cell Level

2021 ◽  
pp. 1-8
Author(s):  
Mengmeng Jiang ◽  
Haide Chen ◽  
Guoji Guo
Keyword(s):  
Molecular Dynamics ◽  
Kidney Disease ◽  
Single Cell ◽  
Kidney Cell ◽  
Single Cell Analysis ◽  
Kidney Diseases ◽  
Treatment Strategies ◽  
Cell Types ◽  
Cellular Heterogeneity ◽  
The Impact

<b><i>Background:</i></b> The kidney is a highly complex organ that performs diverse functions that are essential for health. Kidney disease occurs when the kidneys are damaged and fail to function properly. Single-cell analysis is a powerful technology that provides unprecedented insights into normal and abnormal kidney cell types and will transform our understanding of the mechanism underlying common kidney diseases. <b><i>Summary:</i></b> Our understanding of kidney disease pathogenesis is limited by the incomplete molecular characterization of cell types responsible for kidney functions. Application of single-cell technologies for the study of the kidney has revealed cellular heterogeneity, gene expression signatures, and molecular dynamics during the onset and development of kidney diseases. Single-cell analyses of kidney organoids and allograft tissues offer new insights into kidney organogenesis, disease mechanisms, and therapeutic outcomes. Collectively, a better understanding of kidney cell heterogeneity and the molecular dynamics of kidney diseases will improve diagnostic accuracy and facilitate the identification of novel treatment strategies in nephrology. <b><i>Key Message:</i></b> In this review article, we summarize recent single-cell studies on kidney diseases and discuss the impact of single-cell technology on both basic and clinical nephrology research.

scholarly journals Quantification of single-cell nanoparticle concentrations and the distribution of these concentrations in cell population

2014 ◽  
Vol 11 (94) ◽  
pp. 20131152 ◽  
Author(s):  
Jason T. Rashkow ◽  
Sunny C. Patel ◽  
Ryan Tappero ◽  
Balaji Sitharaman
Keyword(s):  
Single Cell ◽  
Inductively Coupled Plasma ◽  
Single Cell Analysis ◽  
Single Cells ◽  
Large Population ◽  
Cellular Heterogeneity ◽  
Physical Parameters ◽  
Animal Cells ◽  
Promising Tool ◽  
Icp Ms

Quantification of nanoparticle uptake into cells is necessary for numerous applications in cellular imaging and therapy. Herein, synchrotron X-ray fluorescence (SXRF) microscopy, a promising tool to quantify elements in plant and animal cells, was employed to quantify and characterize the distribution of titanium dioxide (TiO 2 ) nanosphere uptake in a population of single cells. These results were compared with average nanoparticle concentrations per cell obtained by widely used inductively coupled plasma mass spectrometry (ICP-MS). The results show that nanoparticle concentrations per cell quantified by SXRF were of one to two orders of magnitude greater compared with ICP-MS. The SXRF results also indicate a Gaussian distribution of the nanoparticle concentration per cell. The results suggest that issues relevant to the field of single-cell analysis, the limitation of methods to determine physical parameters from large population averages leading to potentially misleading information and the lack of any information about the cellular heterogeneity are equally relevant for quantification of nanoparticles in cell populations.

scholarly journals Single-cell analysis of pancreatic ductal adenocarcinoma identifies a novel fibroblast subtype associated with poor prognosis but better immunotherapy response

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Yu Wang ◽  
Yiyi Liang ◽  
Haiyan Xu ◽  
Xiao Zhang ◽  
Tiebo Mao ◽  
...  
Keyword(s):  
Single Cell ◽  
Pancreatic Ductal Adenocarcinoma ◽  
Cancer Cells ◽  
Immune Cells ◽  
Poor Prognosis ◽  
Single Cell Analysis ◽  
Treatment Options ◽  
Objective Response ◽  
Complete Response ◽  
Ductal Adenocarcinoma

AbstractThe current pathological and molecular classification of pancreatic ductal adenocarcinoma (PDAC) provides limited guidance for treatment options, especially for immunotherapy. Cancer-associated fibroblasts (CAFs) are major players of desmoplastic stroma in PDAC, modulating tumor progression and therapeutic response. Using single-cell RNA sequencing, we explored the intertumoral heterogeneity among PDAC patients with different degrees of desmoplasia. We found substantial intertumoral heterogeneity in CAFs, ductal cancer cells, and immune cells between the extremely dense and loose types of PDACs (dense-type, high desmoplasia; loose-type, low desmoplasia). Notably, no difference in CAF abundance was detected, but a novel subtype of CAFs with a highly activated metabolic state (meCAFs) was found in loose-type PDAC compared to dense-type PDAC. MeCAFs had highly active glycolysis, whereas the corresponding cancer cells used oxidative phosphorylation as a major metabolic mode rather than glycolysis. We found that the proportion and activity of immune cells were much higher in loose-type PDAC than in dense-type PDAC. Then, the clinical significance of the CAF subtypes was further validated in our PDAC cohort and a public database. PDAC patients with abundant meCAFs had a higher risk of metastasis and a poor prognosis but showed a dramatically better response to immunotherapy (64.71% objective response rate, one complete response). We characterized the intertumoral heterogeneity of cellular components, immune activity, and metabolic status between dense- and loose-type PDACs and identified meCAFs as a novel CAF subtype critical for PDAC progression and the susceptibility to immunotherapy.

scholarly journals Single-cell proteomic and transcriptomic analysis of macrophage heterogeneity using SCoPE2

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Harrison Specht ◽  
Edward Emmott ◽  
Aleksandra A. Petelski ◽  
R. Gray Huffman ◽  
David H. Perlman ◽  
...  
Keyword(s):  
Single Cell ◽  
Single Cell Analysis ◽  
Single Cells ◽  
Single Cell Protein ◽  
Cellular Heterogeneity ◽  
Cell Protein ◽  
Alternatively Activated Macrophages ◽  
Monocytes And Macrophages ◽  
Molecular Phenotypes ◽  
Post Transcriptional Regulation

Abstract Background Macrophages are innate immune cells with diverse functional and molecular phenotypes. This diversity is largely unexplored at the level of single-cell proteomes because of the limitations of quantitative single-cell protein analysis. Results To overcome this limitation, we develop SCoPE2, which substantially increases quantitative accuracy and throughput while lowering cost and hands-on time by introducing automated and miniaturized sample preparation. These advances enable us to analyze the emergence of cellular heterogeneity as homogeneous monocytes differentiate into macrophage-like cells in the absence of polarizing cytokines. SCoPE2 quantifies over 3042 proteins in 1490 single monocytes and macrophages in 10 days of instrument time, and the quantified proteins allow us to discern single cells by cell type. Furthermore, the data uncover a continuous gradient of proteome states for the macrophages, suggesting that macrophage heterogeneity may emerge in the absence of polarizing cytokines. Parallel measurements of transcripts by 10× Genomics suggest that our measurements sample 20-fold more protein copies than RNA copies per gene, and thus, SCoPE2 supports quantification with improved count statistics. This allowed exploring regulatory interactions, such as interactions between the tumor suppressor p53, its transcript, and the transcripts of genes regulated by p53. Conclusions Even in a homogeneous environment, macrophage proteomes are heterogeneous. This heterogeneity correlates to the inflammatory axis of classically and alternatively activated macrophages. Our methodology lays the foundation for automated and quantitative single-cell analysis of proteins by mass spectrometry and demonstrates the potential for inferring transcriptional and post-transcriptional regulation from variability across single cells.

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